Demetris Nicolaides

Frederick University

Papers

2

Total Citations

99

H-Index

2

About

Demetris Nicolaides is a leading researcher at the intersection of artificial intelligence and sustainable construction, specializing in deep learning applications for waste management and environmental monitoring. His most impactful work focuses on revolutionizing construction and demolition waste (CDW) sorting through real-time object detection systems. In his highly cited 2023 study (95 citations), Nicolaides conducted a comprehensive evaluation of state-of-the-art deep learning models, comparing single-stage and two-stage detectors to optimize the accuracy and speed required for robotic waste sorting. This foundational research directly enables the development of autonomous sorting robots that can identify and separate recyclable materials from mixed waste streams in real time, addressing a critical bottleneck in circular economy practices. His work has significant implications for reducing landfill waste and improving resource recovery in the construction industry. By bridging computer vision and environmental engineering, Nicolaides demonstrates how advanced AI can solve practical sustainability challenges, making his research essential reading for engineers and computer scientists working on smart waste management systems.

Research Focus

Key Achievements

2
H-Index
2
Papers
99
Total Citations
50
Avg Citations/Paper
🏆 Most Cited Paper
Real-time construction demolition waste detection using state-of-the-art deep learning methods; single–stage vs two-stage detectors
95 citations · 2023
📈 Most Prolific Year: 2023 (2 Papers)
🤝 Key Collaborators: 5
🏛 Institutions: Frederick University

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago